On the (in) effectiveness of large language models for chinese text correction

Y Li, H Huang, S Ma, Y Jiang, Y Li, F Zhou… - arXiv preprint arXiv …, 2023 - arxiv.org
Recently, the development and progress of Large Language Models (LLMs) have amazed
the entire Artificial Intelligence community. As an outstanding representative of LLMs and the …

MESED: A multi-modal entity set expansion dataset with fine-grained semantic classes and hard negative entities

Y Li, T Lu, HT Zheng, Y Li, S Huang, T Yu… - Proceedings of the …, 2024 - ojs.aaai.org
The Entity Set Expansion (ESE) task aims to expand a handful of seed entities with new
entities belonging to the same semantic class. Conventional ESE methods are based on …

Grammargpt: Exploring open-source llms for native chinese grammatical error correction with supervised fine-tuning

Y Fan, F Jiang, P Li, H Li - … on Natural Language Processing and Chinese …, 2023 - Springer
Grammatical error correction aims to correct ungrammatical sentences automatically.
Recently, some work has demonstrated the excellent capabilities of closed-source Large …

Lateval: An interactive llms evaluation benchmark with incomplete information from lateral thinking puzzles

S Huang, S Ma, Y Li, M Huang, W Zou, W Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
With the continuous evolution and refinement of LLMs, they are endowed with impressive
logical reasoning or vertical thinking capabilities. But can they think out of the box? Do they …

CLEME: debiasing multi-reference evaluation for grammatical error correction

J Ye, Y Li, Q Zhou, Y Li, S Ma, HT Zheng… - arXiv preprint arXiv …, 2023 - arxiv.org
Evaluating the performance of Grammatical Error Correction (GEC) systems is a challenging
task due to its subjectivity. Designing an evaluation metric that is as objective as possible is …

Correct Like Humans: Progressive Learning Framework for Chinese Text Error Correction

Y Li, S Ma, S Chen, H Huang, S Huang… - Available at SSRN …, 2023 - papers.ssrn.com
Abstract Chinese Text Error Correction (CTEC) aims to detect and correct errors in the input
text, which benefits human daily life and various downstream tasks. Recent approaches …

Gee! grammar error explanation with large language models

Y Song, K Krishna, R Bhatt, K Gimpel… - arXiv preprint arXiv …, 2023 - arxiv.org
Grammatical error correction tools are effective at correcting grammatical errors in users'
input sentences but do not provide users with\textit {natural language} explanations about …

When llms meet cunning questions: A fallacy understanding benchmark for large language models

Y Li, Q Zhou, Y Luo, S Ma, Y Li, HT Zheng, X Hu… - arXiv preprint arXiv …, 2024 - arxiv.org
Recently, Large Language Models (LLMs) have made remarkable evolutions in language
understanding and generation. Following this, various benchmarks for measuring all kinds …

Towards real-world writing assistance: A chinese character checking benchmark with faked and misspelled characters

Y Li, Z Xu, S Chen, H Huang, Y Li, Y Jiang, Z Li… - arXiv preprint arXiv …, 2023 - arxiv.org
Writing assistance is an application closely related to human life and is also a fundamental
Natural Language Processing (NLP) research field. Its aim is to improve the correctness and …

A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Check

H Huang, J Ye, Q Zhou, Y Li, Y Li, F Zhou… - arXiv preprint arXiv …, 2023 - arxiv.org
In recent years, Chinese Spelling Check (CSC) has been greatly improved by designing
task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task …